BrightonSchoolSIM
Spatial Interaction Demand Model for Brighton Schools
Origins - Brighton LSOAs and Pupils in 2024
Reading layer `BrightonLSOA_Clean' from data source
`E:\BH_Schools_2\data\BrightonLSOA_Clean.geojson' using driver `GeoJSON'
Simple feature collection with 165 features and 27 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -0.2450499 ymin: 50.79908 xmax: -0.0160027 ymax: 50.89237
Geodetic CRS: WGS 84Reading layer `lsoa_btn_pw_cent' from data source
`E:\BH_Schools_2\data\lsoa_btn_pw_cent.geojson' using driver `GeoJSON'
Simple feature collection with 165 features and 1 field
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 524624.9 ymin: 102198.2 xmax: 538674.1 ymax: 109563.7
Projected CRS: OSGB36 / British National GridReading layer `LSOA_NOMIS_plus_projections' from data source
`E:\BH_Schools_2\data\LSOA_NOMIS_plus_projections.geojson'
using driver `GeoJSON'
replacing null geometries with empty geometries
Simple feature collection with 3465 features and 5 fields (with 3465 geometries empty)
Geometry type: GEOMETRYCOLLECTION
Dimension: XY
Bounding box: xmin: NA ymin: NA xmax: NA ymax: NA
Geodetic CRS: WGS 84Reading layer `BrightonSecondaryCatchments' from data source
`E:\BH_Schools_2\data\BrightonSecondaryCatchments.geojson'
using driver `GeoJSON'
Simple feature collection with 6 features and 2 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 523887.8 ymin: 100896.4 xmax: 539613.4 ymax: 110190.1
Projected CRS: OSGB36 / British National GridReading layer `optionA' from data source `E:\BH_Schools_2\data\optionA.geojson' using driver `GeoJSON'
Simple feature collection with 6 features and 2 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 523889.3 ymin: 100892.8 xmax: 540295.5 ymax: 110191.6
Projected CRS: OSGB36 / British National GridReading layer `optionB' from data source `E:\BH_Schools_2\data\optionB.geojson' using driver `GeoJSON'
Simple feature collection with 4 features and 2 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 523890.5 ymin: 100894.1 xmax: 539613.1 ymax: 110186.1
Projected CRS: OSGB36 / British National GridDestinations - Brighton Secondary Schools
Interactions
[1] "21"Reading layer `oa_brighton' from data source
`E:\BH_Schools_2\data\oa_brighton.geojson' using driver `GeoJSON'
Simple feature collection with 936 features and 10 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 523598.1 ymin: 101780.1 xmax: 539862.4 ymax: 111919.1
Projected CRS: OSGB36 / British National GridSet up for the travel time matrix
[1] "lsoa21cd" "geometry" "2024" "fid" "lon" "lat" [1] 1650[1] "data.frame"Cost - Travel Time Along the Road Network
Map the flows
Reading layer `catchement_01' from data source
`E:\BH_Schools_2\data\BTN_catchments\Catchment vectorised\catchment_01.geojson'
using driver `GeoJSON'
Simple feature collection with 6 features and 2 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 524022.7 ymin: 101601.6 xmax: 539862.4 ymax: 110470.1
Projected CRS: OSGB36 / British National GridReading layer `catchement_02' from data source
`E:\BH_Schools_2\data\BTN_catchments\Catchment vectorised\catchment_02.geojson'
using driver `GeoJSON'
Simple feature collection with 4 features and 2 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -0.2391914 ymin: 50.79736 xmax: -0.0160027 ymax: 50.87872
Geodetic CRS: WGS 84Reading layer `catchment_03a' from data source
`E:\BH_Schools_2\data\BTN_catchments\Catchment vectorised\catchment_03a.geojson'
using driver `GeoJSON'
Simple feature collection with 8 features and 2 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -0.2391914 ymin: 50.79736 xmax: -0.0160027 ymax: 50.87872
Geodetic CRS: WGS 84Error in wk_handle.wk_wkb(wkb, s2_geography_writer(oriented = oriented, :
Loop 0 is not valid: Edge 45 crosses edge 47Simple feature collection with 165 features and 19 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 524624.9 ymin: 102198.2 xmax: 538674.1 ymax: 109563.7
Projected CRS: OSGB36 / British National Grid
# A tibble: 165 × 20
geography `2021` `2022` `2023` `2024` `2025` `2026` `2027` `2028` `2029`
* <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 E01016958 14.3 13.5 13.4 14.4 13.5 13.9 13.8 13.2 12.6
2 E01016908 26.0 24.5 24.3 26.1 24.5 25.2 25.0 23.9 22.8
3 E01016983 21.4 20.2 20.0 21.5 20.2 20.8 20.6 19.7 18.8
4 E01016989 18.6 17.5 17.4 18.7 17.5 18.1 17.9 17.1 16.3
5 E01016919 13.7 12.9 12.8 13.7 12.9 13.2 13.1 12.6 12.0
6 E01016884 20.7 19.5 19.3 20.8 19.5 20.1 19.8 19.0 18.1
7 E01016941 4.99 4.70 4.66 5.01 4.70 4.84 4.79 4.60 4.38
8 E01016899 8.96 8.44 8.37 9.00 8.44 8.69 8.60 8.25 7.86
9 E01016998 23.3 21.9 21.8 23.4 22.0 22.6 22.4 21.5 20.4
10 E01016925 16.3 15.3 15.2 16.4 15.3 15.8 15.6 15.0 14.3
# ℹ 155 more rows
# ℹ 10 more variables: `2030` <dbl>, `2031` <dbl>, `2024_scaling_fact` <dbl>,
# `2026_scaling_fact` <dbl>, `2030_scaling_fact` <dbl>,
# `2024_scaled_BTN_places` <dbl>, `2026_scaled_BTN_places` <dbl>,
# `2030_scaled_BTN_places` <dbl>, fid <int>, geometry <POINT [m]>Error in wk_handle.wk_wkb(wkb, s2_geography_writer(oriented = oriented, :
Loop 0 is not valid: Edge 45 crosses edge 47Something here to look at PANs vs Places and FSM in 2024 for different catchment options
#first aggregate PAN, FSM etc to each of the different x, a, c, C catchment designs
optionX_stats <- brighton_sec_schools_sml %>%
select(optionX, school_capacity, number_of_pupils, fsm, pan2024, pan2026, pan2030, contains('count')) %>%
group_by(optionX) %>%
summarise(across(where(is.numeric), sum, na.rm = TRUE), .groups = 'drop') %>%
mutate(fsm_pct = round(fsm/number_of_pupils, 2)) %>%
relocate(fsm_pct, .after = fsm) %>%
st_drop_geometry()
optionA_stats <- brighton_sec_schools_sml %>%
select(optionA, school_capacity, number_of_pupils, fsm, pan2024, pan2026, pan2030, contains('count')) %>%
group_by(optionA) %>%
summarise(across(where(is.numeric), sum, na.rm = TRUE), .groups = 'drop') %>%
mutate(fsm_pct = round(fsm/number_of_pupils, 2)) %>%
relocate(fsm_pct, .after = fsm) %>%
st_drop_geometry()
optionB_stats <- brighton_sec_schools_sml %>%
select(optionB, school_capacity, number_of_pupils, fsm, pan2024, pan2026, pan2030, contains('count')) %>%
group_by(optionB) %>%
summarise(across(where(is.numeric), sum, na.rm = TRUE), .groups = 'drop') %>%
mutate(fsm_pct = round(fsm/number_of_pupils, 2)) %>%
relocate(fsm_pct, .after = fsm) %>%
st_drop_geometry()
optionC_stats <- brighton_sec_schools_sml %>%
select(optionC, school_capacity, number_of_pupils, fsm, pan2024, pan2026, pan2030, contains('count')) %>%
group_by(optionC) %>%
summarise(across(where(is.numeric), sum, na.rm = TRUE), .groups = 'drop') %>%
mutate(fsm_pct = round(fsm/number_of_pupils, 2)) %>%
relocate(fsm_pct, .after = fsm) %>%
st_drop_geometry()
#now join the stats back to the catchment polygons
optionX_summarised <- optionX_summarised %>%
left_join(optionX_stats, by = c("catchment" = "optionX"))
optionA_summarised <- optionA_summarised %>%
left_join(optionA_stats, by = c("catchment" = "optionA"))
optionB_summarised <- optionB_summarised %>%
left_join(optionB_stats, by = c("catchment" = "optionB"))
optionC_summarised <- optionC_summarised %>%
left_join(optionC_stats, by = c("catchment" = "optionC"))
# Display the results
# Create the map for optionC
tm_shape(optionA_summarised) +
tm_polygons(
col = "fsm_pct",
popup.vars = c("Catchment" = "catchment", "FSM %" = "fsm_pct"),
palette = "Purples",
title = "FSM %"
) +
tm_layout(
legend.show = TRUE,
title = "Option A"
) +
tm_shape(optionB_summarised) +
tm_polygons(
col = "fsm_pct",
popup.vars = c("Catchment" = "catchment", "FSM %" = "fsm_pct"),
palette = "Purples",
title = "FSM %"
) +
tm_layout(
legend.show = TRUE,
title = "Option B"
) +
tm_shape(optionC_summarised) +
tm_polygons(
col = "fsm_pct",
popup.vars = c("Catchment" = "catchment", "FSM %" = "fsm_pct"),
palette = "Purples",
title = "FSM %"
) +
tm_layout(
legend.show = TRUE,
title = "Option C"
)Work out total commuting time as minutes x pupils for each place in each catchment currently
Picking a distance-decay beta parameter
https://transportgeography.org/contents/methods/spatial-interactions-gravity-model/spatial-interactions-beta-alpha-lambda/
[1] 2560[1] 2560# A tibble: 10 × 2
dest prodSIM1
<chr> <dbl>
1 114579 296.
2 114580 281.
3 114581 176.
4 114606 273.
5 114607 322.
6 114608 234.
7 114611 385.
8 136164 173.
9 137063 199.
10 139409 220. orig dest flow
Length:1650 Length:1650 Min. : 0.03876
Class :character Class :character 1st Qu.: 0.51329
Mode :character Mode :character Median : 0.95700
Mean : 1.55151
3rd Qu.: 1.84295
Max. :18.70974 orig dest flow
Length:1650 Length:1650 Min. : 4.00
Class :character Class :character 1st Qu.: 56.00
Mode :character Mode :character Median : 85.00
Mean : 92.34
3rd Qu.:121.00
Max. :281.00 [1] 1650[1] 1650Gravity Model Longhill
Gravity Model BACA